The Journal of Machine Learning Research
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Predicting response to political blog posts with topic models
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Finding emotion in image descriptions
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Predicting responses to microblog posts
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Unifying local and global agreement and disagreement classification in online debates
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
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Political blogs as a form of social media allow for an uniquely interactive form of political discourse. This is especially evident in focused blogs with a strong ideological identity. We investigate techniques to identify topics within the context of the community, which when discussed in a blog post evoke a discernible positive or negative collective opinion from readers who respond to posts in comments. This is done by using computational methods to assign sentiment polarity to blog comments and learning community specific models that summarize issues tackled by blogs and predict the polarity based on the topics discussed in a blog post.